Abstract
The advent of high-resolution (HR) electrical mapping of slow wave activity has significantly improved the understanding of gastric slow wave activity in normal and dysrhythmic states. One of the current limitations of this technique is it generates a vast amount of data, making manual analysis a tedious task for research and clinical development. In this study we present new automated methods to classify, identify, and locate patterns of interest in gastric slow wave propagation. The classification method uses a similarity metric to classify slow wave propagations, while the identification algorithm uses the divergence and mean curvature of the slow wave propagation to identify and regionalize patterns of interest. The methods were applied to synthetic and experimental datasets and were also compared to manual analysis. The methods classified and identified patterns of slow wave propagation in less than 1 s, compared to manual analysis which took up to 40 min. The automated methods achieved 96% accuracy in classifying AT maps, and 95% accuracy in identifying the propagation pattern with a mean spatial error of 1.5 mm in comparison to manual methods. These new methods will facilitate the efficient translation of gastrointestinal HR mapping techniques to clinical practice.
Similar content being viewed by others
References
Allessie, M. A., W. J. Lammers, I. M. Bonke, and J. Hollen. Intra-atrial reentry as a mechanism for atrial flutter induced by acetylcholine and rapid pacing in the dog. Circulation 70:123–135, 1984.
Angeli, T., G. O. Grady, P. Du, N. Paskaranandavadivel, A. Pullan, I. Bissett, and L. Cheng. Circumferential and functional re-entry of in vivo slow-wave activity in the porcine small intestine. Neurogastroenterol. Motil. 25(5):e304–e314, 2013.
Bull, S., G. O’Grady, L. Cheng, and A. Pullan. A framework for the online analysis of multi-electrode gastric slow wave recordings. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2011, pp. 1741–1744.
Du, P., G. O’Grady, J. Egbuji, W. Lammers, D. Budgett, P. Nielsen, J. Windsor, A. Pullan, and L. Cheng. High-resolution mapping of in vivo gastrointestinal slow wave activity using flexible printed circuit board electrodes: methodology and validation. Ann. Biomed. Eng. 37:839–846, 2009.
Du, P., G. O’Grady, J. Gao, S. Sathar, and L. K. Cheng. Toward the virtual stomach: progress in multiscale modeling of gastric electrophysiology and motility. Wiley Interdiscip. Rev. Syst. Biol. Med. 5(4):481–493, 2013.
Du, P., G. O’Grady, N. Paskaranandavadivel, T. R. Angeli, C. Lahr, T. L. Abell, L. K. Cheng, and A. J. Pullan. Quantification of velocity anisotropy during gastric electrical arrhythmia. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2011, pp. 4402–4405.
Egbuji, J., G. O’Grady, P. Du, L. Cheng, W. Lammers, J. Windsor, and A. Pullan. Origin, propagation and regional characteristics of porcine gastric slow wave activity determined by high-resolution mapping. Neurogastroenterol. Motil. 22:e292–e300, 2010.
Erickson, J., G. O’Grady, P. Du, J. Egbuji, A. Pullan, and L. Cheng. Automated gastric slow wave cycle partitioning and visualization for high-resolution activation time maps. Ann. Biomed. Eng. 39:469–483, 2011.
Erickson, J., G. O’Grady, P. Du, C. Obioha, W. Qiao, W. Richards, L. Bradshaw, A. Pullan, and L. Cheng. Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in high-resolution serosal electrode recordings. Ann. Biomed. Eng. 38:1511–1529, 2010.
Fitzgerald, T., D. Brooks, and J. Triedman. Identification of cardiac rhythm features by mathematical analysis of vector fields. IEEE Trans. Biomed. Eng. 52:19–29, 2005.
Gray, A., E. Abbena, and S. Salamon. Modern Differential Geometry of Curves and Surfaces With Mathematica. Boca Raton: Chapman & Hall, 2006.
Grover, M., C. Bernard, P. Pasricha, M. Lurken, M. Faussone-Pellegrini, T. Smyrk, H. Parkman, T. Abell, W. Snape, and W. Hasler. Clinical-histological associations in gastroparesis: results from the gastroparesis clinical research consortium. Neurogastroenterol. Motil. 24:531–e249, 2012.
Huizinga, J., and W. Lammers. Gut peristalsis is governed by a multitude of cooperating mechanisms. Am. J. Physiol. Gastrointest. Liver Physiol. 296:G1–G8, 2009.
Kay, M. W., and R. A. Gray. Measuring curvature and velocity vector fields for waves of cardiac excitation in 2-D media. IEEE Trans. Biomed. Eng. 52:50–63, 2005.
Koch, K. The electrifying stomach. Neurogastroenterol. Motil. 23:815–818, 2011.
Lammers, W. Arrhythmias in the gut. Neurogastroenterol. Motil. 25:353–357, 2013.
Lammers, W. J., L. Ver Donck, B. Stephen, D. Smets, and J. A. Schuurkes. Focal activities and re-entrant propagations as mechanisms of gastric tachyarrhythmias. Gastroenterology 135:1601–1611, 2008.
Lammers, W., L. Ver Donck, B. Stephen, D. Smets, and J. A. Schuurkes. Origin and propagation of the slow wave in the canine stomach: the outlines of a gastric conduction system. Am. J. Physiol. Gastrointest. Liver Physiol. 296:G1200–G1210, 2009.
Lees-Green, R., P. Du, G. O’Grady, A. Beyder, G. Farrugia, A. Pullan. Biophysically based modeling of the interstitial cells of Cajal: current status and future perspectives. Front. Physiol. 2:29, 2011.
Lien, H. C., W. M. Sun, Y.-H. Chen, H. Kim, W. Hasler, and C. Owyang. Effects of ginger on motion sickness and gastric slow-wave dysrhythmias induced by circular vection. Am. J. Physiol. Gastrointest. Liver Physiol. 284:G481–G489, 2003.
Lin, Z., E. Y. Eaker, I. Sarosiek, and R. W. McCallum. Gastric myoelectrical activity and gastric emptying in patients with functional dyspepsia. Am. J. Gastroenterol. 94:2384–2389, 1999.
McCallum, R. W., W. Snape, F. Brody, J. Wo, H. P. Parkman, and T. Nowak. Gastric electrical stimulation with Enterra therapy improves symptoms from diabetic gastroparesis in a prospective study. Clin. Gastroenterol. Hepatol. 8:947–954, 2010.
Meyer, F. Topographic distance and watershed lines. Signal Process. 38:113–125, 1994.
O’Grady, G., T. Angeli, P. Du, C. Lahr, W. Lammers, J. Windsor, T. Abell, G. Farrugia, A. Pullan, and L. Cheng. Abnormal initiation and conduction of slow-wave activity in gastroparesis, defined by high-resolution electrical mapping. Gastroenterology 143:589–598, 2012.
O’Grady, G., P. Du, L. Cheng, J. Egbuji, W. Lammers, J. Windsor, and A. Pullan. Origin and propagation of human gastric slow-wave activity defined by high-resolution mapping. Am. J. Physiol. Gastrointest. Liver Physiol. 299:G585–G592, 2010.
O’Grady, G., P. Du, J. U. Egbuji, W. J. Lammers, A. Wahab, A. J. Pullan, L. K. Cheng, and J. A. Windsor. A novel laparoscopic device for measuring gastrointestinal slow-wave activity. Surg. Endosc. 23:2842–2848, 2009.
O’Grady, G., P. Du, N. Paskaranandavadivel, T. Angeli, W. Lammers, S. Asirvatham, J. Windsor, G. Farrugia, A. Pullan, and L. Cheng. Rapid high-amplitude circumferential slow wave propagation during normal gastric pacemaking and dysrhythmias. Neurogastroenterol. Motil. 24:e299–e312, 2012.
O’Grady, G., J. Egbuji, P. Du, W. Lammers, L. Cheng, J. Windsor, and A. Pullan. High-resolution spatial analysis of slow wave initiation and conduction in porcine gastric dysrhythmia. Neurogastroenterol. Motil. 23:e345–e355, 2011.
Owyang, C., and W. Hasler. Physiology and pathophysiology of the interstitial cells of Cajal: from bench to bedside. VI. Pathogenesis and therapeutic approaches to human gastric dysrhythmias. Am. J. Physiol. Gastrointest. Liver Physiol. 283:G8, 2002.
Parkman, H., W. Hasler, J. Barnett, and E. Eaker. Electrogastrography: a document prepared by the gastric section of the american motility society clinical GI motility testing task force. Neurogastroenterol. Motil. 15:89–102, 2003.
Paskaranandavadivel, N., L. K. Cheng, P. Du, G. O’Grady, and A. J. Pullan. Improved signal processing techniques for the analysis of high resolution serosal slow wave activity in the stomach. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2011, pp. 1737–1740.
Paskaranandavadivel, N., G. O’Grady, P. Du, A. J. Pullan, and L. K. Cheng. An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping. IEEE Trans. Biomed. Eng. 59:882–889, 2012.
Paskaranandavadivel, N., G. O’Grady, P. Du, and L. K. Cheng. Comparison of filtering methods for extracellular gastric slow wave recordings. Neurogastroenterol. Motil. 25:79–83, 2013.
Pogwizd, S. M., R. Hoyt, J. Saffitz, P. Corr, J. Cox, and M. Cain. Reentrant and focal mechanisms underlying ventricular tachycardia in the human heart. Circulation 86:1872–1887, 1992.
Rogers, J. M., M. Usui, B. H. KenKnight, R. E. Ideker, and W. M. Smith. A quantitative framework for analyzing epicardial activation patterns during ventricular fibrillation. Ann. Biomed. Eng. 25:749–760, 1997.
Rogers, J. M., M. Usui, B. H. KenKnight, R. E. Ideker, and W. M. Smith. Recurrent wavefront morphologies: a method for quantifying the complexity of epicardial activation patterns. Ann. Biomed. Eng. 25:761–768, 1997.
Shenasa, M., G. Hindricks, M. Borggrefe, and G. Breithardt. Cardiac Mapping, 4th ed. Oxford: Wiley-Blackwell, 2009.
Yassi, R., G. O’Grady, N. Paskaranandavadivel, P. Du, T. Angeli, A. Pullan, L. Cheng, and J. Erickson. The gastrointestinal electrical mapping suite (GEMS): software for analyzing and visualizing high-resolution (multi-electrode) recordings in spatiotemporal detail. BMC Gastroenterol. 12:60, 2012.
Acknowledgments
This work was supported in part by funding from the NZ Health Research Council (New Zealand) and the, NIH R01 grant (R01 DK64775). JG was supported by a University of Auckland Health Research Doctoral Scholarship, a Freemasons Postgraduate Scholarship, and a R. H. T. Bates Postgraduate Scholarship. PD was supported by a New Zealand Postdoctoral Fellowship and a Marsden Fast-Start grant.
Author information
Authors and Affiliations
Corresponding author
Additional information
Associate Editor Leonidas D Iasemidis oversaw the review of this article.
Electronic supplementary material
Below is the link to the electronic supplementary material.
AVI (11385 KB)
Rights and permissions
About this article
Cite this article
Paskaranandavadivel, N., Gao, J., Du, P. et al. Automated Classification and Identification of Slow Wave Propagation Patterns in Gastric Dysrhythmia. Ann Biomed Eng 42, 177–192 (2014). https://doi.org/10.1007/s10439-013-0906-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10439-013-0906-3